| Stance Detection with Bidirectional Conditional Encoding I Augenstein, T Rocktäschel, A Vlachos, K Bontcheva EMNLP 2016, 2016 | 563 | 2016 |
| SemEval 2017 Task 10: ScienceIE-Extracting Keyphrases and Relations from Scientific Publications I Augenstein, M Das, S Riedel, L Vikraman, A McCallum International Workshop on Semantic Evaluation (SemEval) 2017, 2017 | 507 | 2017 |
| Latent multi-task architecture learning S Ruder, J Bingel, I Augenstein, A Søgaard Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4822-4829, 2019 | 478 | 2019 |
| emoji2vec: Learning Emoji Representations from their Description B Eisner, T Rocktäschel, I Augenstein, M Bošnjak, S Riedel SocialNLP Workshop at EMNLP 2016, 2016 | 435 | 2016 |
| MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims I Augenstein, C Lioma, D Wang, LC Lima, C Hansen, C Hansen, ... EMNLP 2019, 2019 | 365 | 2019 |
| A simple but tough-to-beat baseline for the Fake News Challenge stance detection task B Riedel, I Augenstein, GP Spithourakis, S Riedel arXiv preprint arXiv:1707.03264, 2017 | 348 | 2017 |
| A Diagnostic Study of Explainability Techniques for Text Classification P Atanasova, JG Simonsen, C Lioma, I Augenstein EMNLP 2020, 2020 | 340 | 2020 |
| Generating Fact Checking Explanations P Atanasova, JG Simonsen, C Lioma, I Augenstein ACL 2020, 2020 | 323 | 2020 |
| QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension A Rogers, M Gardner, I Augenstein ACM Computing Surveys (CSUR), 2022 | 315 | 2022 |
| Factuality challenges in the era of large language models and opportunities for fact-checking I Augenstein, T Baldwin, M Cha, T Chakraborty, GL Ciampaglia, D Corney, ... Nature Machine Intelligence, 1-12, 2024 | 286 | 2024 |
| Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence A Holzinger, M Dehmer, F Emmert-Streib, R Cucchiara, I Augenstein, ... Information Fusion 79, 263-278, 2022 | 239 | 2022 |
| Learning what to share between loosely related tasks S Ruder, J Bingel, I Augenstein, A Søgaard arXiv preprint arXiv:1705.08142, 2017 | 230 | 2017 |
| Probing Pre-Trained Language Models for Cross-Cultural Differences in Values A Arora, LA Kaffee, I Augenstein C3NLP @ EACL 2023, 2023 | 198 | 2023 |
| A Survey on Stance Detection for Mis- and Disinformation Identification M Hardalov, A Arora, P Nakov, I Augenstein NAACL 2022, 2022 | 183 | 2022 |
| A Survey on Gender Bias in Natural Language Processing K Stanczak, I Augenstein arXiv preprint arXiv:2112.14168, 2021 | 176 | 2021 |
| Discourse-aware rumour stance classification in social media using sequential classifiers A Zubiaga, E Kochkina, M Liakata, R Procter, M Lukasik, K Bontcheva, ... Information Processing & Management 54 (2), 273-290, 2018 | 175 | 2018 |
| Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM E Kochkina, M Liakata, I Augenstein International Workshop on Semantic Evaluation (SemEval) 2017, 2017 | 171 | 2017 |
| LODifier: generating linked data from unstructured text I Augenstein, S Padó, S Rudolph The Semantic Web: Research and Applications, 210-224, 2012 | 167 | 2012 |
| Generalisation in named entity recognition: A quantitative analysis I Augenstein, L Derczynski, K Bontcheva Computer Speech & Language 44, 61-83, 2017 | 157 | 2017 |
| Detecting Harmful Content on Online Platforms: What Platforms Need vs. Where Research Efforts Go A Arora, P Nakov, M Hardalov, SM Sarwar, V Nayak, Y Dinkov, D Zlatkova, ... ACM Computing Surveys, 2023 | 141* | 2023 |
Arnav AroraUniversity of CopenhagenVerified email at di.ku.dk
